Evaluate the robustness and performance between ML and DL models in predicting the CPC concentration under various image capturing devices, types of input image datasets, and lighting conditions. The findings in our current study can overcome the bottleneck by eliminating the need for laborious manual extraction processes and reducing the time and

The findings in the present study will be a breakthrough for the estimation of CPC concentration from S. platensis solely based on the information provided in the image without the need to perform a prior extraction process and identification of CPC concentration using analytical equipment.

Covered Advanced Machine Learning topics like hyperparameter tuning for Machine Learning techniques, GridSearchCV, Pruning, Linear SVM Regressor, Polynomial Kernel SVM Regressor, Bayesian Network Analysis etc,.

Predicting diamond prices using various regression algorithms. This project involves data preprocessing, feature engineering, and model evaluation to determine the best predictor for diamond prices.

IoT and ML to assuage the uncertainty in city bus schedules. Track live running status and avail tentative schedule of buses. Minimal IoT setup with a central ML-driven web-backend.

India is one of the countries with the highest air pollution country. Generally, air pollution is assessed by PM value or air quality index value. For my further analysis, I have selected PM-2.5 value to determine the air quality prediction and the India-Bangalore region. Also, the data was collected through web scraping with the help of Beautif…

This repository contains implementations of popular machine learning algorithms including Support Vector Machine (SVM), Decision Tree, and Naive Bayes. Each algorithm is implemented separately, providing clear and concise examples of their usage for classification tasks.

- Notebook for car price prediction using regression models.

Predict stock Closing price for the next day

PySVM : A NumPy implementation of SVM based on SMO algorithm. Numpy构建SVM分类、回归与单分类，支持缓存机制与随机傅里叶特征

A collection of machine learning models for predicting laptop prices

The "House-Price-Prediction" repository contains code for a model that predicts house prices. It considers factors like bedrooms, bathrooms, and living area. With simple instructions, With the help of this model we can easily predict results as per our requirement.

Predicted the sales price using different machine learning prediction models for Housing Prices Dataset

Boston house price prediction using Linear Regression.

This project aims to develop a machine learning model to predict bike-sharing demand based on various factors such as weather conditions, time of day, and historical usage patterns. The dataset used for this project consists of 8760 records and 14 attributes.

This repository contains code for predicting stock prices using various machine learning models. The models implemented include Linear Regression, SVM Regression, KNN Regression, Kernel Ridge Regression, and Ridge Regression.

The goal of this project is to predict the demand for Seoul's Bike Sharing Program. A dataset (8760,14) containing historical usage patterns, such as temperature, time, and other relevant data is used to build a regression model.

Team student project for Pattern recognition course.

Ranking Reviews Based on their utility using Advanced NLP Techniques